Exploring data from genetic association studies using bayesian variable selection and the dirichlet process: application to searching for gene × gene patterns.

TitleExploring data from genetic association studies using bayesian variable selection and the dirichlet process: application to searching for gene × gene patterns.
Publication TypeJournal Article
Year of Publication2012
AuthorsPapathomas M, Molitor J, Hoggart C, Hastie D, Richardson S
JournalGenet Epidemiol
Volume36
Issue6
Pagination663-74
Date Published2012 Sep
ISSN1098-2272
Abstract

We construct data exploration tools for recognizing important covariate patterns associated with a phenotype, with particular focus on searching for association with gene-gene patterns. To this end, we propose a new variable selection procedure that employs latent selection weights and compare it to an alternative formulation. The selection procedures are implemented in tandem with a Dirichlet process mixture model for the flexible clustering of genetic and epidemiological profiles. We illustrate our approach with the aid of simulated data and the analysis of a real data set from a genome-wide association study.

DOI10.1002/gepi.21661
Alternate JournalGenet. Epidemiol.
PubMed ID22851500